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How Waahtsy Analyzes Your Skills for Better Job Matches.

 



Waahtsy uses a combination of advanced algorithms and intelligent features to analyze your skills and provide highly relevant job recommendations. Here’s how the process works:

1. Profile and Skill Extraction

·       Natural Language Processing (NLP): Waahtsy uses NLP to interpret the information you enter in your profile—such as skills, qualifications, and work experience. This technology extracts key details from your resume and any additional information you provide, ensuring a comprehensive understanding of your capabilities.

·       Multiple Skill Profiles: You can create detailed profiles for different types of jobs (white-collar, blue-collar, gig work), allowing the system to match you with a wider range of opportunities.

2. Automated Matching Algorithms

·       Keyword and Semantic Matching: The platform goes beyond simple keyword matching by using semantic analysis. This means it understands the context and meaning of your skills and compares them with job descriptions to find the best fit.

·       Machine Learning Models: Waahtsy leverages machine learning algorithms that learn from historical data—such as successful job placements and user preferences—to continuously improve the accuracy of its recommendations.

3. Personalized Recommendation Engine

·       Criteria-Based Filtering: The system allows you to set preferences (location, job type, salary, etc.), and uses these filters along with your skill profile to narrow down relevant opportunities.

·       Real-Time Notifications: You receive alerts when new jobs match your profile, thanks to continuous data analysis and real-time updates.

4. Continuous Feedback and Learning

·       User Feedback Integration: The platform incorporates your feedback (such as ratings and application outcomes) to refine its matching process, ensuring that future recommendations align even better with your preferences and skills.

·       Application Tracking and Analytics: Waahtsy tracks your application history and engagement, using this data to further personalize job suggestions.

5. Advanced Techniques (Industry Standard)

While Waahtsy does not publicly disclose every technical detail, industry-standard platforms often use:

·       Vectorization of Skills and Job Descriptions: Transforming your profile and job listings into numerical representations for more precise matching.

·       K-Nearest Neighbors (KNN) and Regression Models: These algorithms help rank and score how well your skills align with job requirements.

In summary: Waahtsy analyzes your skills using a mix of NLP, machine learning, semantic search, and real-time data processing. This ensures you receive job matches that are tailored to your unique abilities and preferences, helping you find the most suitable opportunities quickly and efficiently.

⁂

1.       https://hackerearth.com/blog/ai-enhanced-job-matching-finding-the-perfect-fit  

2.       https://www.mokahr.io/myblog/ai-powered-job-match-algorithms/    

3.       https://www.waahtsy.net/job-search    

4.      https://www.waahtsy.net/part-time-jobs 

5.       https://www.jobspikr.com/blog/job-matching-algorithm/

6.      https://www.techrxiv.org/users/869020/articles/1277349-machine-learning-for-recruitment-analyzing-job-matching-algorithms

7.       https://www.techrxiv.org/users/869020/articles/1277349/master/file/data/Machine learning for recruitment Analyzing job matching algorithms/Machine learning for recruitment Analyzing job matching algorithms.pdf

8.      https://scholarworks.sjsu.edu/context/faculty_rsca/article/2408/viewcontent/Enhanced_Algorithmic_Job_Matching_based_on_a_Comprehensive_Candidate_Profile_using_NLP_and_Machine_Learning.pdf 

9.      https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5086025

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